class_docstr: Decision List Classifier
  
  Currently a slight variant of SkopeRules from skope-rules.
  https://github.com/scikit-learn-contrib/skope-rules
code: def _scores(self, X):
      df = pd.DataFrame(X, columns=self.feature_index_)
      selected_rules = self.internal_rules_
  
      scores = np.ones(X.shape[0]) * np.inf
      for k, r in enumerate(selected_rules):
          matched_idx = list(df.query(r[0]).index)
          scores[matched_idx] = np.minimum(k, scores[matched_idx])
      scores[np.isinf(scores)] = len(selected_rules)
      scores = scores.astype("int64")
  
      return scores
  
imports: from itertools import count
  from sklearn.base import ClassifierMixin
  from sklearn.utils.validation import check_is_fitted
  from ..api.base import ExplainerMixin, ExplanationMixin
  from ..utils._explanation import gen_name_from_class, gen_global_selector, gen_local_selector, gen_perf_dicts
  from copy import deepcopy
  import numpy
  import pandas
  import re
  from ..utils._clean_x import preclean_X
  from ..utils._clean_simple import clean_dimensions, typify_classification
  from ..utils._unify_data import unify_data
  import logging
label_desc: Use image node_id 4 for calling the DecisionListClassifier obj's underlying member method code with example usage: obj._scores(X) and returns: scores